The two most popular languages in data science are R and Python. The number of data science libraries present in both these languages is overwhelming. As a result, a newcomer to data science spends most of their energy learning the syntax of these libraries rather than spending time in mastering the underlying concepts.
The idea while creating this repository, which contains data science code recipes in R and Python both, was to help newcomers quickly get going in this field.
Before starting to use the code recipes, the first thing is to familiarie yourself with the file structure and the code structure of the repository. Only then you'd be able judge how to use it and put the code to its full use.
Here's one way to use this repository - after learning a concept, say, data cleaning strategies, look for its code in the language that you're interested in and then use it directly, or customize it before using it.